Intelligent and autonomous agents is a subarea of symbolic artificial intelligence where these agents decide, either reactively or proactively, upon a course of action by reasoning about the information that is available about the world (including the environment, the agent itself, and other agents). It encompasses a multitude of techniques, such as negotiation protocols, agent simulation, multi-agent argumentation, multi-agent planning, and many others. In this paper, we focus on agent programming and we provide a systematic review of the literature in agent-based programming for multi-agent systems. In particular, we discuss both veteran (still maintained) and novel agent programming languages, their extensions, work on comparing some of these languages, and applications found in the literature that make use of agent programming.

The advent of sophisticated robotics and AI technology makes sending humans into hazardous and distant environments to carry out inspections increasingly avoidable. Being able to send a robot, rather than a human, into a nuclear facility or deep space is very appealing. However, building these robotic systems is just the start and we still need to carry out a range of verification and validation tasks to ensure that the systems to be deployed are as safe and reliable as possible. Based on our experience across three research and innovation hubs within the UK’s “Robots for a Safer World” programme, we present an overview of the relevant techniques and challenges in this area. As the hubs are active across nuclear, offshore, and space environments, this gives a breadth of issues common to many inspection robots.

Purpose of Review: The deployment of hardware (e.g., robots, satellites, etc.) to space is a costly and complex endeavor. It is of extreme importance that on-board systems are verified and validated through a variety of verification and validation techniques, especially in the case of autonomous systems. In this paper, we discuss a number of approaches from the literature that are relevant or directly applied to the verification and validation of systems in space, with an emphasis on autonomy.Recent Findings: Despite advances in individual verification and validation techniques, there is still a lack of approaches that aim to combine different forms of verification in order to obtain system-wide verification of modular autonomous systems.Summary: This systematic review of the literature includes the current advances in the latest approaches using formal methods for static verification (model checking and theorem proving) and runtime verification, the progress achieved so far in the verification of machine learning, an overview of the landscape in software testing, and the importance of performing compositional verification in modular systems. In particular, we focus on reporting the use of these techniques for the verification and validation of systems in space with an emphasis on autonomy, as well as more general techniques (such as in the aeronautical domain) that have been shown to have potential value in the verification and validation of autonomous systems in space.